18 research outputs found

    Interleaved Parton Showers and Tuning Prospects

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    General-purpose Monte Carlo event generators have become important tools in particle physics, allowing the simulation of exclusive hadronic final states. In this article we examine the Pythia 8 generator, in particular focusing on its parton-shower algorithms. Some relevant new additions to the code are introduced, that should allow for a better description of data. We also implement and compare with 2 to 3 real-emission QCD matrix elements, to check how well the shower algorithm fills the phase space away from the soft and collinear regions. A tuning of the generator to Tevatron data is performed for two PDF sets and the impact of first new LHC data is examined

    Hadronic final states in deep-inelastic scattering with Sherpa

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    We extend the multi-purpose Monte-Carlo event generator Sherpa to include processes in deeply inelastic lepton-nucleon scattering. Hadronic final states in this kinematical setting are characterised by the presence of multiple kinematical scales, which were up to now accounted for only by specific resummations in individual kinematical regions. Using an extension of the recently introduced method for merging truncated parton showers with higher-order tree-level matrix elements, it is possible to obtain predictions which are reliable in all kinematical limits. Different hadronic final states, defined by jets or individual hadrons, in deep-inelastic scattering are analysed and the corresponding results are compared to HERA data. The various sources of theoretical uncertainties of the approach are discussed and quantified. The extension to deeply inelastic processes provides the opportunity to validate the merging of matrix elements and parton showers in multi-scale kinematics inaccessible in other collider environments. It also allows to use HERA data on hadronic final states in the tuning of hadronisation models.Comment: 32 pages, 22 figure

    Scaling Patterns for QCD Jets

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    Jet emission at hadron colliders follows simple scaling patterns. Based on perturbative QCD we derive Poisson and staircase scaling for final state as well as initial state radiation. Parton density effects enhance staircase scaling at low multiplicities. We propose experimental tests of our theoretical findings in Z+jets and QCD gap jets production based on minor additions to current LHC analyses.Comment: 36 pages, 16 figure

    Standard Model backgrounds to supersymmetry searches

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    This work presents a review of the Standard Model sources of backgrounds to the search of supersymmetry signals. Depending on the specific model, typical signals may include jets, leptons, and missing transverse energy due to the escaping lightest supersymmetric particle. We focus on the simplest case of multijets and missing energy, since this allows us to expose most of the issues common to other more complex cases. The review is not exhaustive, and is aimed at collecting a series of general comments and observations, to serve as guideline for the process that will lead to a complete experimental determination of size and features of such SM processes.Comment: To appear in the J. Wess memorial volume, "Supersymmetry on the Eve of the LHC", to be published in European Physical Journal

    The automated computation of tree-level and next-to-leading order differential cross sections, and their matching to parton shower simulations

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    Energy-aware very fast decision tree

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    Recently machine learning researchers are designing algorithms that can run in embedded and mobile devices, which introduces additional constraints compared to traditional algorithm design approaches. One of these constraints is energy consumption, which directly translates to battery capacity for these devices. Streaming algorithms, such as the Very Fast Decision Tree (VFDT), are designed to run in such devices due to their high velocity and low memory requirements. However, they have not been designed with an energy efficiency focus. This paper addresses this challenge by presenting the nmin adaptation method, which reduces the energy consumption of the VFDT algorithm with only minor effects on accuracy. nmin adaptation allows the algorithm to grow faster in those branches where there is more confidence to create a split, and delays the split on the less confident branches. This removes unnecessary computations related to checking for splits but maintains similar levels of accuracy. We have conducted extensive experiments on 29 public datasets, showing that the VFDT with nmin adaptation consumes up to 31% less energy than the original VFDT, and up to 96% less energy than the CVFDT (VFDT adapted for concept drift scenarios), trading off up to 1.7 percent of accuracy
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